| An effective approach for rotor electrical asymmetry detection in wind turbine DFIGs RK Ibrahim, SJ Watson, S Djurović, CJ Crabtree IEEE Transactions on Industrial Electronics 65 (11), 8872-8881, 2018 | 64 | 2018 |
| Neural networks for wind turbine fault detection via current signature analysis R Ibrahim, J Weinert, S Watson Loughborough University, 2016 | 40 | 2016 |
| Digital quality management systems: benefits and challenges R Ibrahim Proceedings on Engineering Sciences 1 (2), 163-172, 2019 | 13 | 2019 |
| Anomaly detection for large hydrogenerators using the variational autoencoder based on vibration signals R Ibrahim, R Zemouri, A Tahan, F Lafleur, B Kedjar, A Merkhouf, ... 2022 International Conference on Electrical Machines (ICEM), 1609-1615, 2022 | 9 | 2022 |
| Effect of power converter on condition monitoring and fault detection for wind turbine RK Ibrahim, S Watson IET Digital Library, 2016 | 9 | 2016 |
| Stator winding fault diagnosis in synchronous generators for wind turbine applications RK Ibrahim, S Watson IET Digital Library, 2016 | 9 | 2016 |
| Advanced algorithms for wind turbine condition monitoring and fault diagnosis R Ibrahim, S Watson Loughborough University, 2016 | 6 | 2016 |
| Wind turbine simulation model for the study of combined mechanical and electrical faults R Ibrahim, S Watson Loughborough University, 2015 | 5 | 2015 |
| Condition monitoring of permanent magnet synchronous generator for wind turbine applications RK Ibrahim, S Watson 2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol), 648-653, 2016 | 4 | 2016 |
| Effective algorithms for real-time wind turbine condition monitoring and fault-detection R Ibrahim Loughborough University, 2020 | 1 | 2020 |
| Adaptive fault detection and tracking for a wind turbine generator using Kalman filter R Ibrahim, A Daniyan, S Watson ASRANet Ltd, 2016 | | 2016 |
| ONLINE NONINTRUSIVE CONDITION MONITORING AND FAULT PROGNOSIS FOR WIND R Ibrahim, S Watson | | |
